NBA Early-Career Competition Analysis
Objective
Examine how rookie- and sophomore-year positional competition affects NBA lottery picks’ scoring trajectories over their first five seasons. Positional competition measures how crowded a player’s role is on their team.
Key Findings
★ Sophomore-year competition has the largest impact. Players with more positional competition in their second season start with slightly higher scoring averages but exhibit flatter or declining growth after Year 3.
★ Rookie-year competition has a modest effect. Higher competition in the first season slightly boosts baseline points per game but does not meaningfully alter scoring trajectories.
★ After accounting for individual- and team-level factors, early-career competition influences both short- and long-term scoring development. While it may accelerate initial performance, it can limit growth later in a player’s career.
Methods
Data: Player stats from Basketball Reference, cleaned and processed in Python and R.
Model: Linear mixed-effects model capturing player-level differences over time.
Validation: Confidence intervals and diagnostics ensured reliable estimates.
Visualization: Interactive plots of predicted scoring trajectories.
Why It Matters
The methods used here can be applied beyond sports analytics, in areas such as:
Finance: Modeling portfolio growth under varying conditions.
Healthcare: Tracking patient outcomes over time under different treatments.
Education: Evaluating student performance trajectories across learning environments.
Deep Dive
The full analysis including data processing, model building, and detailed results is available: